We empirically compare registration models trained with the unsupervised \(\operatorname{DeepSim_{ae}}\)  and semi-supervised \(\operatorname{DeepSim_{seg}}\)  to the baselines \(\operatorname{MSE}\) , \(\operatorname{NCC}\) , \(\operatorname{NCC_{sup}}\)  (\(\operatorname{NCC}\)  with supervised information), and \(\operatorname{VGG}\)  (a VGG-net based deep similarity metric from image generation). Our implementation of the baseline methods follows [1]}, [2]}, and [3]}.
